declared
0.00Data from "Milder winters alleviate seasonal challenges for a migratory goose facing Arctic warming"
Geisler, Jan · Rakhimberdiev, Eldar · Boom, Michiel P. · et al.
29 files · 124 MB · csv, shapefiledeclared
hybrid · semantic + lexical · 31 datasets ranked · 0.78s
Geisler, Jan · Rakhimberdiev, Eldar · Boom, Michiel P. · et al.
29 files · 124 MB · csv, shapefiledeclared
1. Many migratory birds now reach their Arctic breeding grounds earlier in order to keep pace with advancing springs and shifting nutrient peaks, either by departing earlier from non-breeding grounds or by travelling faster. For dark-bellied brent geese, there is limited potential to travel faster, as their migration to the Siberian breeding grounds is already among the fastest of Arctic geese and swans. Earlier departure would require reaching departure body mass earlier, either through a faster accumulation of energy stores during spring staging or via adjustments earlier in the annual cycle. 2. We examined long-term shifts in spring staging phenology and changes in winter and spring body mass trajectories of brent geese at the population level, with particular emphasis on the effects of winter temperature on body mass and spring body mass on departure timing. 3. We used more than five decades of body mass measurements from individuals caught in the United Kingdom and France, and in the Dutch Wadden Sea to reconstruct changes in spring and winter mass trajectories, respectively. These data were combined with over five decades of migration counts in the Netherlands and more than two decades of counts in Denmark to quantify changes in spring staging phenology. 4. We found that brent geese have not shifted their spring arrival in the Wadden Sea but have advanced departure timing. Furthermore, brent geese were heavier during and after milder winters, and have changed mass trajectories over recent decades. They no longer lose mass during winter and the second spring staging phase, and fuelling rates in the first spring staging phase have declined. Annual variation in body mass was not related to annual departure timing. 5. These results suggest that milder winters have relaxed energetic constraints and improved body condition in brent geese throughout the non-breeding season. Our findings highlight the importance of considering the full annual cycle when assessing how animals with limited capacity to adjust migration timing or speed respond to global change.
Kavanagh, Jack · Anthony, Patrick
6 files · 11 MB · geojson, geopackage, shapefiledeclared
A historical map showing a segment of the boundaries of New Spain in c. 1800. This map is fully open to fellow researchers and is available in multiple open source formats (SHP, GPKG, GeoJSON).
Kavanagh, Jack · Anthony, Patrick
6 files · 9.3 MB · geojson, geopackage, shapefiledeclared
A historical map of the boundaries of Prussia in c. 1795. This map is fully open to fellow researchers and is available in multiple open source formats (SHP, GPKG, GeoJSON).
Costes, Jean C.
28 files · 8.0 GB · fitsdeclared
Stellar activity is the main barrier to detecting and/or confirming low-mass/long-period (and Earth-analogue) planets using radial-velocity (RV) measurements. Searching forreliable indicatorsthat bettertrace magnetic activity may be key for both distinguishing more clearly between stellar and planetary signals, and for probing the underlying physics occurring on the stellar surface. In this work we have compared observations taken for magnetically active and inactive stellar phases over multiple time-scales to study the spectral imprint due to varying stellar activity. This serves as a proof-of-concept demonstration of a technique (named Spectral Ratio Analysis, SRA) that can be used to isolate activity-driven changes directly in the stellar photospheric absorption lines where RVs are measured. Using 14 relatively quiet and well sampled G- and K-type starsthatshow stellar activity cycles, we identified hundreds of activity-sensitive spectral features. Reducing this variability information into two global metrics - amplitude and velocity shift - uncovers potential evidence of a decoupling of the photospheric and chromospheric responsesto stellar activity in earlier-type stars. Additionally, potential signatures of the variations in the magnitude of the suppression of the convective blueshift throughout the activity cycle were observed via SRA. Finally, we show that these SRA indicators better capture RV variability than classical activity proxies, such as the chromospheric log R HK index and other cross-correlation function-based parameters such as bisector span and full width at half-maximum, by up to a factor of two. The direct link between photospheric line behaviour and stellar-induced RV variability offers a promising path for improving astrophysical noise mitigation. In these files you will find for each star a .fits file in which the seasonal and nightly difference spectra and its associated SDATemplate are given per order. Their respective errors have been added as well. Finally, the wavelength for each order, as well as the seasonal and nightly bjd of each observation and its measured logRHK are availbale in these files. Additionally, a .txt file have been added for each star showing the atlas of all the SDA detected features. The wavelength of each feature, its amplitude, its width and its potentially associated lines obtained from VALD are given in these files.
Francescone, Marco
14 files · 380 KB · shapefile, zipdeclared
This dataset contains original geomorphic mapping of surface fault traces along the Dixie Valley Fault (DVF) range front and piedmont zone, central Nevada, USA. Traces were mapped directly from a 1-m bare-earth lidar digital elevation model (DEM), using hillshade and slope-raster visualizations. This dataset accompanies the manuscript: Francescone, M., et al. (in review), LiDAR-Based Fault-Scarp Analysis and Rupture Hazard Assessment: Earthquake Scenarios of the Dixie Valley Fault System (Nevada, USA). See Section 3.1 ("Fault Trace Mapping") of the manuscript for full methodological details
Meekes, Lisa · Tabaro, Francesco · Bexkens, Michiel · et al.
41 files · 8.2 GB · csv, fasta, pdfdeclared
This record contains the Python software for PEPTiGEN, a tool for generating tryptic peptides from prokaryotic gene sequences and their variants, and the associated antimicrobial resistance (AMR) peptide database. The database is provided as an SQL file and a CSV file containing all genes and predicted peptides. The README file contains explanation of the PEPTiGEN tool. The SQL database schema files contains both the database schema of the SQL database used in the PEPTiGEN analysis as the database schema of the AMR peptide datbase.
Dey, Hemal · Shao, Wanyun
14 files · 5.5 MB · csv, jpeg, shapefiledeclared
Despite the proliferation of social vulnerability assessment methodologies, selecting the most appropriate model remains a critical challenge due to inter-model variability. To explore the inter-model variability, this study systematically investigated inter-algorithmic and inter-classification variability to assess how methodological design influences outcomes.
Cheng, Yuhan · Bai, Lubin · Zhang, Xiuyuan · et al.
15 files · 140 MB · shapefile, zipdeclared
Data used in the paper "Annotation-Efficient Building Footprint Updating via Historical Map Reuse and Iterative Instance Segmentation"
Ye, Renhao · Shen, Shiyin
65 files · 46 GB · csv, fits, tardeclared
Part 15 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 59.1-78.7°, Dec -39.9--24.9°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
67 files · 46 GB · csv, fits, tardeclared
Part 14 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 62-archive subset (RA 45.0-70.2°, Dec -48.1--30.1°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
66 files · 46 GB · csv, fits, tardeclared
Part 13 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 61-archive subset (RA 51.5-81.5°, Dec -54.3--30.0°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
64 files · 46 GB · csv, fits, tardeclared
Part 12 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 59-archive subset (RA 34.0-213.7°, Dec -66.5-80.4°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Goedkoop, Willem · Fölster, Jens · Lau, Danny Chun Pong · et al.
16 files · 145 KB · shapefiledeclared
Main scripts for assessing satellite data using rgee. The loops can run slowly, so testing may require using smaller regions.
Walker, Matthew Gregory
4 files · 8.9 GB · fits, gzipdeclared
Data files, see Appendix of for description of contents
Mimet, Anne · Gourmemon, Damien · Amandine, Vergondy · et al.
14 files · 1.6 GB · shapefile, tiffdeclared
================================================================================ README ================================================================================ Dataset Title: Observation points, movement-proxy data, and high-resolution land cover map for the common blackbird ( Turdus merula ) in Angers, France Version: 1.0 Authors : Mimet, Anne ; Gourmelon Damien ; Oulhen, Thomas ; Vergondy, Amandine Date of biological data collection: Observation points : 15/05/2025 to 06/06/2025 Movement-proxy data : 19/04/2024 to 17/05/2024 -------------------------------------------------------------------------------- DESCRIPTION -------------------------------------------------------------------------------- This dataset contains observed presence/absence of blackbird flights across streets, as well as point observations of the common blackbird across Angers, France, during spring. The data were used to create a connectivity model for the common blackbird in Angers. The 68 point observations provided information on the land cover types used as a possible resource by the common blackbird. The presence/absence of flying blackbirds across 190 streets in Munich was used to derive the resistance of the urban landscape to the movement of common blackbirds in a landscape connectivity model. For the point observations, the presence and absence of the common blackbird was visually and acoustically confirmed after 5 minutes of observations within a radius of 25 m. Movement presence/absence was observed along 50 m street transects. Street transects were observed for 9 minutes, and the presence or absence of common blackbirds crossing this street was recorded. The observation points and movement-proxy data were selected along gradients of greenness and traffic density. -------------------------------------------------------------------------------- FILE LIST -------------------------------------------------------------------------------- 1. movement_proxy.shp Site-level data containing presence and absence of common blackbirds crossing the sampled streets, as well as covariates such as the number of pedestrians passing during the sampling period, geographic information, information on the weather, time of sampling, pseudonomized observer. Number of records: 190 Number of variables: 11 related files: movement_proxy.cpg, movement_proxy.dbf, movement_proxy.prj, movement_proxy.shp, movement_proxy.shx The related files are required because data is stored in a shapefile. For this shapefile to be correctly read by any GIS processing software, all related files need to be saved in the same folder. 2. point_observations.shp Site-level data containing presence and absence of common blackbirds at the observation points. Additionally, geographic and temporary information as well as information on the weather are provided. Number of records: 68 Number of variables: 10 related files: point_observations.cpg, point_observations.dbf, point_observations.prj, point_observations.shp, point_observations.shx The related files are required because data is stored in a shapefile. For this shapefile to be correctly read by any GIS processing software, all related files need to be saved in the same folder. 3. LULC_9Class_Angers.tif and assoociated qlm style file Land use and land cover map at 40 cm resolution for Angers. 3. README.txt This file. -------------------------------------------------------------------------------- VARIABLE DESCRIPTIONS: movement_proxy.shp -------------------------------------------------------------------------------- StreetCod Site identifier for street transect - these are the same sites as in the file Point_observations.shp (format: [text]) X Northing coordinate of the centre (latitude) (format: [degree]) Y Easting coordinate of the observation point (longitude) (format: [degree]) Obs Id of the observor (2 observors in the dataset) date Date of the observation (format [%d/%m/%y]) Daytime Starting time of observation (format: [text] hour%h%min) Windspeed Windspeed given by the mobile phone application « Accuweather » Temperatur Temperature at the time of observation in °C given by the mobile phone application « Accuweather » Pedestrian Number of pedestrians combined passing by during the time of observation CarDensity Number of cars counted on a 3-min period FlyBbird Number of common blackbirds Turdus merula that crossed the street transect during the time of observation (9 min). Every crossing event was counted. When the same individual crossed 2 times, it was counted 2 times -------------------------------------------------------------------------------- VARIABLE DESCRIPTIONS: point_observations.shp -------------------------------------------------------------------------------- StreetCod Site identifier for street transect - this are the same sites as in the file movement_proxy.shp (format: [text]) X Northing coordinate of observation point (latitude) (format: [degree]). Y Easting coordinate of the observation point (longitude) (format: [degree]) Obs Id of the observor (1 in this dataset) date Date of the observation (format [%d/%m/%y]) Daytime Starting time of observation (format: [text] hour%h%min) Windspeed Windspeed given by the mobile phone application « Accuweather » Temperatur Temperature at the time of observation in °C given by the mobile phone application « Accuweather » AbBlackb Number of common blackbirds Turdus merula that were detected by sight or sound during the 5-min observatin période, over a radius of 25 m. PABlackb Presence-Absence of observed blackbirds derived from the abundance. -------------------------------------------------------------------------------- VARIABLE DESCRIPTIONS: LULC_9Class_Angers.tif -------------------------------------------------------------------------------- 11 : Buildings < 5m 12 : Buildings 5-10m 13 : Buildings 10-18m 14 : Buildings > 18m 20 : Sealed areas 31 : vegetation < 1m 32 : Vegetation 1-3m 33 : Vegetation > 3m 40 : Farmland 50 : Bare soil 60 : Water -------------------------------------------------------------------------------- METHODS SUMMARY -------------------------------------------------------------------------------- Site Selection for Movement-Proxy Data: - 190 sites selected via stratified random sampling across vegetation cover (computed in a radius of 300m around the points) and traffic density (derived from TomTom navigation data for October 2022) - Observations along 50 m street transects - Detection of presence/absence of common blackbirds crossing the sampled streets Site Selection for Point Observations: - 68 sites selected via stratified random sampling across vegetation cover (computed in a radius of 300m around the points) and traffic density (derived from TomTom navigation data for October 2022) - Visual and acoustic detection of presence/absence of common blackbirds within a 25 m radius LULC map: Derived from land cover information from CoSIA (IGN 2023a), refined with a digital terrain model (IGN 2020) and height model (IGN 2023b) to extract building and vegetation height classes. -------------------------------------------------------------------------------- RELATED PUBLICATIONS -------------------------------------------------------------------------------- Lisa Merkens*, Meret Pundsack*, Anne Mimet*, Damien Gourmelon, Wolfgang W. Weisser. City-specific or generalisable resistances? An urban animal connectivity model performs better when parameterised from two cities. Preprint Submitted to Urban Ecosystems -------------------------------------------------------------------------------- FUNDING -------------------------------------------------------------------------------- Région Pays de la Loire through the PULSAR project VitalConnect (2024_05894 ) -------------------------------------------------------------------------------- LICENSE -------------------------------------------------------------------------------- This dataset is licensed under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). You are free to: - Share: copy and redistribute the material in any medium or format - Adapt: remix, transform, and build upon the material for any purpose Under the following terms: - Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. Full license text: https://creativecommons.org/licenses/by/4.0/ -------------------------------------------------------------------------------- CITATION -------------------------------------------------------------------------------- If you use this dataset, please cite both the dataset and the associated publication: Dataset: Mimet, A., Gourmelon, D, Oulhen, T., Vergondy, A. (2026) Observation points, movement-proxy data, and high-resolution land cover map for the common blackbird (Turdus merula) in Angers, France [Dataset]. Zenodo. Publication: Lisa Merkens*, Meret Pundsack*, Anne Mimet*, Damien Gourmelon, Wolfgang W. Weisser. City-specific or generalisable resistances? An urban animal connectivity model performs better when parameterised from two cities. Preprint Submitted to Urban Ecosystems -------------------------------------------------------------------------------- CONTACT -------------------------------------------------------------------------------- Anne Mimet Université d'Angers Laboratoire BiodivAG, DEP ENS SCIENCES Biologie, UFR SCIENCES 2 Boulevard de Lavoisier, F-49045 Angers, France Email: anne.mimet@univ-angers.fr ORCID: 0000-0001-9498-436X ================================================================================ END OF README ================================================================================
Kavanagh, Jack · Anthony, Patrick
6 files · 1.5 MB · geojson, geopackage, shapefiledeclared
A historical map of the boundaries of the Kazakh Steppe in c. 1848. This map is fully open to fellow researchers and is available in multiple open source formats (SHP, GPKG, GeoJSON).
Ye, Renhao · Shen, Shiyin
69 files · 47 GB · csv, fits, tardeclared
Part 2 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 64-archive subset (RA 137.7-270.0°, Dec 52.9-79.9°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
65 files · 46 GB · csv, fits, tardeclared
Part 3 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 180.0-270.0°, Dec 68.7-80.3°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
66 files · 46 GB · csv, fits, tardeclared
Part 4 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 61-archive subset (RA 84.4-285.5°, Dec -41.4-80.4°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.
Ye, Renhao · Shen, Shiyin
65 files · 46 GB · csv, fits, tardeclared
Part 5 of 20. Synthetic Euclid VIS-band galaxy images generated from DESI Legacy Imaging Surveys r,z-band cutouts using an Image-to-Image Schrödinger Bridge (I2SB) model, over the Euclid Q1 footprint. The full processed dataset covers 2,981,033 FITS cutouts packed into 1,235 tar archives grouped by HEALPix sky pixel (nside=64, NESTED ordering), ~1 GB each. Because Zenodo limits each record to 100 files and 50 GB, the full set is split across 20 records. This record publishes a 60-archive subset (RA 47.7-93.4°, Dec -67.7--16.7°). Integrity and provenance: checksums.tsv and desi2euclid_index.csv record the SHA256 of all 1,235 archives from this processing run, not just the ones published as downloadable files here. These values let this exact version of the data be independently verified in the future -- including before any analysis built on it has been published -- by recomputing an archive's SHA256 and comparing it against the recorded value, to confirm the file has not been modified, corrupted, or substituted since it was originally produced. See README.md for the FITS layout (predicted VIS image, DESI g,r,z input -- of which only r,z were used to generate the prediction -- and prediction-uncertainty map), how to locate the archive for a given sky position, and how to run the integrity check.